Plasma biomarkers in patients with familial cavernous malformation and their first-degree relatives

Background We aimed to explore the differences in plasma biomarker levels between patients with familial cerebral cavernous malformations (FCCM) and their healthy first-degree relatives (FDRs) and between FCCM patients with and without severe chronic disease aggressiveness (CDA). Methods Magnetic resonance imaging (MRI) scanning and genetic testing was performed in patients with multiple CCMs and their FDRs. Sixty-seven plasma biomarkers were tested using a customised multiplex bead immunoassay kit. Univariate and multivariate unconditional logistic regression analyses were conducted to determine the associations between plasma factors and the risk of developing FCCM and severe CDA. Receiver operating characteristic (ROC) curves were generated for each independent risk factor. Results Plasma factors of 37 patients with FCCM and 37 FDRs were examined. Low CD31 (P < 0.001) and BDNF levels (P = 0.013) were independent risk factors for FCCM. The best model was achieved by combining the results of CD31 and BDNF (AUC = 0.845, sensitivity 0.838, specificity 0.784, cutoff score − 4.295) to distinguish patients with FCCM from healthy FDRs. Low serpin E1/PAI-1 (P = 0.011) and high ROBO4 levels (P = 0.013) were independent risk factors for severe CDA in patients with FCCM. The best model was achieved by combining the results of E1/PAI-1 and ROBO4 levels (AUC = 0.913, sensitivity 1.000, specificity 0.760, cutoff score – 0.525) to identify patients with FCCM and severe CDA. Conclusions The plasma concentrations of CD31 and BDNF seem to be lower in patients with FCCM than in their healthy FDRs. Low serpin E1/PAI-1 and high ROBO4 concentrations may be correlated with high lesion burden and risk of recurrent bleeding.

Plasma biomarkers in patients with familial cavernous malformation and their rst-degree relatives Chunwang

Introduction
Cerebral cavernous malformations (CCMs) are abnormally clustered, dilated capillary caverns lined by a single layer of leaky endothelium 1 .Most CCM cases comprise sporadic CCMs.Hereditary or familial CCM (FCCM) is caused by an autosomal dominant inherited genetic mutation associated with multiple lesions 2 .Three protein-encoding genes, viz.CCM1/KRIT1,CCM2/malcavernin, and CCM3/PDCD10, are known to cause FCCM 3,4 .However, the clinical behavior of CCM remains unpredictable.Some patients remain asymptomatic, while others are disabled due to recurrent bleeding or a high lesion burden or a combination of both 5 .Early detection using biomarkers may improve the outcome of patients with CCM.
However, the molecular mechanisms in uencing and predictive biomarker for chronic or acute disease severity remain largely unknown.
Based on recent discoveries that implicate angiogenic, immune, and in ammatory mechanisms in CCM, some authors have proposed that serum biomarkers may re ect chronic or acute disease activity 6 .Girard et al. pioneered the study of the predictive value of a panel of 24 candidate plasma biomarkers, each with a reported role in the physiopathology of CCMs, to predict clinically relevant disease activity 7,8 .According to their results, the participants who had experienced symptomatic lesional hemorrhagic expansion had low sCD14, IL-6, and VEGF levels and high IL-1 and sROBO4 plasma levels 8 .Recently, Roberto Latini et al revealed sROBO4, thrombomodulin (TM) and CRP can predict incident adverse clinical events 9 .However, no signi cant association was observed between the burden of CCMs and biomarker plasma levels in the FCCM cohort; the predictive model of lesional activity was not derived from a pure FCCM cohort.However, familial cases with germline mutations are generally associated with a greater lesion burden and hemorrhagic risk.
Therefore, this study aimed to explore the differences in plasma biomarker levels between patients with FCCM and their healthy rst-degree blood relatives (FDRs) and between FCCM patients with mild and severe chronic disease aggressiveness (CDA) to identify and stratify patients with FCCM using a new panel of 67 selected candidate plasma biomarkers.

Study objects
Patient with multiple CCM and their FDRs were enrolled our studies in the First A liated Hospital of Fujian Medical University between October 2020 and August 2021.Patients with multiple CCM were enrolled and FDRs screening procedures were previously described 10 .Patients with multiple CCMs and their FDRs were recruited after providing written informed consent for brain MRI scanning, blood sample collection and gene testing.According to the currently accepted categorization [11][12][13] , familial cases were de ned as CCM patients with germline loss-of-function mutations in the CCM complex proteins or with a family history of CCM in FDRs.In an FCCM family, FDRs of either the proband or newly identi ed CCM patients were screened by MRI.
Based on the pedigree investigation, brain MRI scanning, and whole-exome sequencing (WES), the probands and FDRs with CCM were assigned to the CCM group, and healthy FDRs were assigned to the non-CCM group.Screening of participants, collection of clinical information and de nition of severe chronic disease aggressiveness The process of patient screening and inclusion, as well as the collection of information, has been previously described 10 .The information was electronically stored in a secure database (Real Data EDC system) for subsequent analysis.Patients were classi ed as mild and severe CDA, and the latter referred to those who meet any of the following criteria: (1) experiencing symptomatic hemorrhage by the age of 18; (2) experiencing more than one symptomatic hemorrhage event; (3) showing more than 25 lesions on SWI, or more than 5 lesions on T2-weighted images (Fig. 1).Adjudication of the classi cation was performed by the senior author of this study, who was blinded from any information on the biomarker levels.

Assessment of plasma biomarker levels
Candidate biomarkers were selected based on their reported roles in angiogenesis, in ammation, endothelial cell integrity and permeability, cell adhesion, and extracellular matrix remodeling (Supplemental Table 1) 8, [15][16][17][18] .All blood samples were collected using standard clinical 5ml heparinized vacutainer tubes.The use of heparinized plasma to quantify biological compounds was in agreement with clinical practice and the instructions provided by the bio-assay kit manufacturer (Milliplex Human Cytokine kit; Millipore Corp., Billerica, MA).Fasting was not required because the clinical visits were conducted at various times of the day.For plasma isolation, 5 ml of heparinized blood was centrifuged at 3000 rpm for 5 min.The supernatant plasma was aliquoted into microcentrifuge tubes (500 µl) and stored at − 80°C.Sixty-seven plasma biomarkers were assessed using a commercial multiplex bead immunoassay kit (Milliplex Human Cytokine Kit; Millipore Corp., Billerica, MA, USA).Measurements were performed using a Bio-Plex suspension array system (Bio-Plex200; Bio-Rad, Hercules, CA, USA).All the plasma samples used in this study were processed and tested in the same batch.The concentration levels of plasma factors below the limit of detection were replaced by the limit of detection divided by the square root of 2.

Statistical analysis
First, normal analysis was performed using the Shapiro-Wilk test on quantitative data, including demographic data, clinical characteristics, and plasma factors.Most of the data showed a skewed distribution; medians and interquartile ranges were used to describe these data.Quantitative data were compared between two groups using the Mann-Whitney U test.Categorical variables were descriptively summarized as numbers (%), and distribution differences between groups were calculated using the chisquare test or Fisher's test.The correlations between plasma factors were analysed with Spearman's rank correlation coe cient.Second, logistic regression analyses were performed to determine the associations between plasma factors and the risk of CCM occurrence and severe CDA.Variables with P < 0.05 in the univariate analysis were selected for inclusion in a multivariate logistic model (Backwald: Wald).Third, receiver operating characteristic (ROC) curves were generated, and the area under the curve (AUC) was calculated for each plasma factor and in linear combination (discriminant score).The best model was de ned as the one for which the AUC value was greatest, and the optimal cut-off value which provides the best tradeoff between sensitivity and speci city was found using the Youden index method.Finally, generalized linear mixed models (GLMM) were used for sensitivity analysis, de ning the individual level as low level 1 and pedigree level as high level 2. Analyses were performed using SPSS (version 26.0; R version 4.1.0)and GraphPad Prism (version 8.0).Two-tailed P-values < 0.05 were considered statistically signi cant.

Results
Twenty-one multiple CCM patients and their FDRs were screened to identify FCCM families.Based on the MRI scanning, gene testing, and family history survey, 4 patients with neither germline mutations in the CCM1/KRIT1, CCM2/malcavernin, or CCM3/PDCD10 genes nor a family history of CCM were de ned as sporadic CCM cases.The remaining 17 multiple CCM patients were identi ed as index cases of FCCM families.The initial symptoms noted in the 17 probands were hemorrhage in 5 patients (29.4%), epilepsy in 5 patients (29.4%), headache in 2 patients (11.8%), functional neurological de cit (FND) in 1 patient (5.9%), and fever in 1 patient (5.9%), and incidentally spotted by MRI in 3 patients (17.6%).Among a total of 86 participants from the 17 FCCM families, two without intact MRI images, four with suspected CCMs and two with arteriovenous malformations on SWI, one with acute intracerebral hemorrhage on MRI and three who refused to draw blood were all excluded.Finally, the plasma biomarker candidates were examined in the CCM group consisted of 37 FCCM patients and the non-CCM group consisted of 37 healthy FDRs (Fig. 2).
The discriminant ability of the discriminant score established using the GLMM (AUC = 0.915, sensitivity = 1.000, speci city = 0.822) agreed with and supported the logistic regression results mentioned above.

Discussion
The plasma levels of molecules re ecting proliferative dysangiogenesis, blood-brain barrier hyperpermeability, in ammatory/immune processes, and measures of vascular permeability and iron deposition on magnetic resonance imaging are important biomarkers correlated with CCM occurrence and bleeding [6][7][8]19 . In 021, the American NIH/NINDS published the protocol of their study on biomarkers of cerebral cavernous angioma with symptomatic hemorrhage (CASH) to optimize these biomarkers to accurately diagnose CCM with symptomatic hemorrhage (R01NS114552) 20 .However, until now, none of the biomarkers have shown an association with de novo lesion genesis and symptomatic hemorrhage in FCCM cases.Patients with FCCM with small non-aggressive multiple lesions are usually managed conservatively 2 .Nevertheless, invasive intervention in multifocal FCCM cases, although controversial, can be justi able when these lesions become symptomatic or develop.Thus, development and validation of a biomarker model to predict the occurrence and clinical activity of FCCMs may play a direct role in selecting patients with FCCM for aggressive therapies and in the strati cation of cohorts in future clinical trials.To the best of our knowledge, this study is the rst to investigate the differences in plasma biomarker levels between FCCM patients and their healthy FDRs and between FCCM patients with and without severe CDA in a large panel of 67 candidate plasma biomarkers.We found that low CD31and BDNF levels were independent risk factors associated with the occurrence of FCCM; the best model was achieved by combining the results of CD31 and BDNF (AUC = 0.845).Furthermore, serpin E1/PAI-1 and high ROBO4 levels were independent risk factors associated with severe CDA in patients with FCCM, and the best model was achieved by combining the results of E1/PAI-1 and ROBO4 (AUC = 0.913).
Patients and healthy FDRs have similar genetic backgrounds and lifestyles.Therefore, the signi cant differences in plasma concentrations of CD31 and BNDF might be related to the pathogenesis of CCM.
The past two decades have witnessed a remarkable enhancement of our understanding of the pathogenesis of this vascular disease.In FCCM, lesion formation is initiated by a somatic mutation in the CCM gene, resulting in biallelic loss of function, and a secondary somatic gain-of-function mutation in PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha), which fuels lesion growth 21,22 .As a ligand, BDNF-induced TrkB activation of the PI3-kinase and Akt-mTOR pathway may mediate a reduction in EC-cell contacts and in normal EC apoptosis, leading to the development of FCCMs 23,24 .BDNF is best characterized for its pro-survival and differentiative effects on neurons; additionally, studies have uncovered the contribution of the cerebral microvasculature to BDNF production in the brain 25,26 .BDNF de ciency can lead to a reduction in endothelial cell-cell contacts 27 .However, whether the reduction in plasma BDNF concentration in FCCM patients is due to excessive utilization of BDNF remains unknown and could not be clari ed in this study.CD31 is a cell-cell adhesion glycoprotein that belongs to the immunoglobulin superfamily 28,29 .CD31 is not only an endothelial marker but is also involved in the regulation of endothelial cell-cell interactions and angiogenesis 30,31 .The observation that the anti-CD31 antibody blocks the initiation of EC-EC contact suggests an important role of CD31 in maintaining the structural integrity of the EC layer 32 .A previous study showed that murine hemangioendothelioma cells expressed lower levels of CD31 and other components of adherent junctions than wild-type brain endothelial cells (BECs) 33 .BECs with CD31 de ciency (isolated from CD31-knockout mice) would in part mimic the phenotypes of cultured hemangioendothelioma cells, exhibiting an "overriding" morphology, a higher secondary proliferation rate due to the loss of contact inhibition, and a reduced level of apoptosis 33,34 .It was demonstrated that in addition to disrupted tight junction integrity, CD31-de ciency resulted in a perturbation of adhesion molecule-mediated signaling, which affected proliferation and suppressed apoptosis 33,34 , suggesting one of the molecular mechanisms underlying endothelial cell behaviors when vascular anomalies develop in hemangiomas.
Owing to the popularity of MRI, the use of CD31 and BDNF scores to distinguish patients with FCCM from healthy FDRs has little clinical signi cance.However, this score may serve as a biomarker for patient screening and a warning for FCCM occurrence at an early stage.Whether CD31 and BDNF are related to the mechanism of FCCM and whether they can serve as targets for medical intervention requires further research.
An early age of lesion onset, multiple hemorrhages, and increased lesion burden have been de ned as severe chronic disease severity in various studies 6,35 37,38 .This protein has been shown to dynamically maintain vascular network stability during pathological angiogenesis and proin ammatory processes 39,40 .In the FCCM cohort, an increase in plasma ROBO4 levels may re ect pro-in ammatory processes enhancing endothelial permeability, consistent with its prognostic association with CCM bleeding and growth 8 .E1/PAI-1 is a fast-acting inhibitor of tissue and urokinase plasminogen activators (tPA and uPA) 41 .PAI-1 controls the clot lysis triggered by tPA-activated plasminogen.PAI-1 de ciency is characterized by hyper brinolysis, which results in frequent bleeding episodes.Patients with this condition form normal blood clots, which are quickly lysed by unopposed tPA-activated plasmin.Spontaneous bleeding is rare in PAI-1 de cient patients, but moderate hemorrhage of the knees, elbows, nose, and gums can be triggered by mild trauma 42 .In the context of FCCM, lower plasma levels of E1/PAI-1 maybe associated with more frequent cerebral bleeding and a larger hemorrhage volume after ictus.However, the role of E1/PAI-1 in CCM lesion development and hemorrhage requires further investigation.In our study, age was higher in the severe CDA group than in the mild CDA group (P = 0.008) in the univariate analysis (Supplemental

Limitations
Our single-site study did not exclude a referral bias.Future multi-site studies are needed to better control and circumvent these potential biases in a su cient number of cases, if not all.In addition, the correlations herein do not imply a speci c causality related to CCM.However, they resulted in a cogent hypotheses about the mechanism of disease occurrence and progression that can be pursued in future laboratory and clinical studies.Finally, the limitations of the assay methodologies and batch effects must be considered in clinical practice.However, in this study, we investigated the differences in plasma biomarker levels between FCCM patients and their FDRs and between FCCM patients with and without

Figures
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Figure 2 Patients 3 a
Figure 2

Figure 4 a
Figure 4
7,Acute hemorrhage and epileptic seizures have a signi cant in uence on plasma factor concentrations; therefore, they were excluded from this study.The molecular mechanisms in uencing chronic disease severity have not yet been elucidated, and there are currently no known peripheral blood biomarkers that re ect or predict disease aggressiveness in the FCCM population.Recently, several plasma factors, including 25-hydroxyvitamin D, non-HDL cholesterol, IL-2, INF-γ, TNF-α, IL-1β, MMP-2, and − 9, intercellular adhesion molecule-1, VEG, and endoglin, have been proposed to monitor disease severity and the course of sporadic CCMs7,36.Furthermore, the weighted linear combination of soluble CD14, IL-1β, VEGF, and soluble ROBO4 can be used to predict symptomatic ICH or lesion expansion 8 .ROBO4 is an endogenous inhibitor of VEGF signaling expressed by vascular endothelial cells

Table 3 )
. Variables with P < 0.05 in the univariate analysis, including age, serpin E1/PAI-1, ROBO4, IL-7, and BDNF, were selected for inclusion in a multivariate logistic model.However, age was eliminated from the backward model, and only Serpin E1/PAI-1 and ROBO4 were retained in the nal model.In addition, It can be observed that the improvement in age for the model was limited.Overall, we found that the combination of E1/PAI-1 and ROBO4 was the best model to distinguish FCCM patients with mild and severe CDA; therefore, it may be helpful in the prognostication and strati cation of FCCM cases in future clinical trials.